ABSTRACT: Heart disease remains one of the leading causes of mortality worldwide, accounting for millions of deaths annually. Early detection of individuals at risk is essential for reducing ...
1 School of Computing and Data Science, Wentworth Institute of Technology, Boston, USA. 2 Department of Computer Science and Quantitative Methods, Austin Peay State University, Clarksville, USA. 3 ...
The rapid uptake of supervised machine learning (ML) in clinical prediction modelling, particularly for binary outcomes based on tabular data, has sparked debate about its comparative advantage over ...
Introduction: This study investigates the influence of latent categories of professional identity on learning engagement among teacher education students. Methods: Latent Profile Analysis (LPA) was ...
Abstract: This paper presents a novel methodology for employing multisine waveforms in simultaneous wireless information and power transfer (SWIPT) systems, utilizing software-defined radio tools. The ...
Abstract: Hypertension is a critical global health concern, necessitating accurate prediction models and effective prescription decisions to mitigate its risks. This study proposes a hybrid machine ...
Background: Perioperative venous thromboembolism (VTE) is a severe complication in lung cancer surgery. Traditional prediction models have limitations in handling complex clinical data, whereas ...
Summer learning loss, also known as the “summer slide,” represents a significant challenge in education where students experience academic regression during extended breaks from formal instruction.
Logistic Regression is a widely used model in Machine Learning. It is used in binary classification, where output variable can only take binary values. Some real world examples where Logistic ...
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